Automatic classification of heartbeats using wavelet neural network
| Autor: | Radhwane Benali, Zinedine Hadj Slimane, Fethi Bereksi Reguig |
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| Rok vydání: | 2010 |
| Předmět: |
Male
Wavelet neural network Heartbeat Computer science Speech recognition Feature extraction Wavelet Analysis Medicine (miscellaneous) Health Informatics WNN QRS Cardiac arrhythmia QRS complex Electrocardiography Wavelet Health Information Management Image Processing Computer-Assisted Humans cardiovascular diseases Cardiac status Aged Aged 80 and over business.industry ECG Pattern recognition Arrhythmias Cardiac Middle Aged Classification cardiovascular system Female Artificial intelligence Neural Networks Computer business Classifier (UML) Algorithms Information Systems |
| Zdroj: | Journal of medical systems. 36(2) |
| ISSN: | 0148-5598 |
| Popis: | The electrocardiogram (ECG) signal is widely employed as one of the most important tools in clinical practice in order to assess the cardiac status of patients. The classification of the ECG into different pathologic disease categories is a complex pattern recognition task. In this paper, we propose a method for ECG heartbeat pattern recognition using wavelet neural network (WNN). To achieve this objective, an algorithm for QRS detection is first implemented, then a WNN Classifier is developed. The experimental results obtained by testing the proposed approach on ECG data from the MIT-BIH arrhythmia database demonstrate the efficiency of such an approach when compared with other methods existing in the literature. |
| Databáze: | OpenAIRE |
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